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Register a new userNeural Network-Based Generation of Sport Summaries: A Preliminary Study
الجيل القائم على الشبكة العصبية من الملخصات الرياضية: دراسة أولية
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تقدم هذه الورقة طريقة تلخيص عالمية لتعليقات الرياضة الحية التي لدينا ملخص مكتوب بشري متاح.تستند هذه الطريقة إلى ملخص مولد عصبي.يتم تقييد كمية البيانات المتاحة للتدريب مقارنة بالشريعة المستخدمة عادة من قبل الملخصات العصبية.نقترح لمساعدة الملخص على التعلم من كمية محدودة من البيانات عن طريق الحد من انتروبيا من نصوص الإدخال.يتم تنفيذ هذه الخطوة من خلال تصنيف إلى فئات مستمدة من تحليل مفصل للملخصات التي كتبها الإنسان.نظهر أن الترشيح يساعد نظام التلخيص للتغلب على نقص الموارد.ومع ذلك، ظهرت عدة نقاط تحسين من هذه الدراسة الأولية، والتي نناقشها وتخطط لتنفيذها في العمل في المستقبل.
This paper presents a global summarization method for live sport commentaries for which we have a human-written summary available. This method is based on a neural generative summarizer. The amount of data available for training is limited compared to corpora commonly used by neural summarizers. We propose to help the summarizer to learn from a limited amount of data by limiting the entropy of the input texts. This step is performed by a classification into categories derived by a detailed analysis of the human-written summaries. We show that the filtering helps the summarization system to overcome the lack of resources. However, several improving points have emerged from this preliminary study, that we discuss and plan to implement in future work.
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